| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 55 | | tagDensity | 0.236 | | leniency | 0.473 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 92.06% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1260 | | totalAiIsmAdverbs | 2 | | found | | 0 | | | 1 | | adverb | "barely above a whisper" | | count | 1 |
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| | highlights | | 0 | "loosely" | | 1 | "barely above a whisper" |
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| 100.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 76.19% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1260 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "familiar" | | 1 | "tension" | | 2 | "whisper" | | 3 | "silence" | | 4 | "warmth" | | 5 | "traced" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 0 | | maxInWindow | 0 | | found | (empty) | | highlights | (empty) | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 98 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 98 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 139 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 46 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1259 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 16 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 22 | | wordCount | 921 | | uniqueNames | 7 | | maxNameDensity | 0.98 | | worstName | "Lucien" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Lucien" | | discoveredNames | | Ptolemy | 3 | | Moreau | 2 | | Aurora | 5 | | Lucien | 9 | | Frenchman | 1 | | Brick | 1 | | Lane | 1 |
| | persons | | 0 | "Ptolemy" | | 1 | "Moreau" | | 2 | "Aurora" | | 3 | "Lucien" | | 4 | "Frenchman" |
| | places | | | globalScore | 1 | | windowScore | 0.833 | |
| 70.63% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 63 | | glossingSentenceCount | 2 | | matches | | 0 | "quite human" | | 1 | "felt like home" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1259 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 139 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 63 | | mean | 19.98 | | std | 20.69 | | cv | 1.036 | | sampleLengths | | 0 | 40 | | 1 | 38 | | 2 | 69 | | 3 | 1 | | 4 | 21 | | 5 | 5 | | 6 | 4 | | 7 | 64 | | 8 | 4 | | 9 | 9 | | 10 | 9 | | 11 | 17 | | 12 | 57 | | 13 | 57 | | 14 | 5 | | 15 | 6 | | 16 | 9 | | 17 | 2 | | 18 | 30 | | 19 | 3 | | 20 | 9 | | 21 | 52 | | 22 | 9 | | 23 | 1 | | 24 | 2 | | 25 | 15 | | 26 | 6 | | 27 | 2 | | 28 | 4 | | 29 | 34 | | 30 | 8 | | 31 | 10 | | 32 | 9 | | 33 | 2 | | 34 | 37 | | 35 | 38 | | 36 | 4 | | 37 | 8 | | 38 | 28 | | 39 | 3 | | 40 | 41 | | 41 | 1 | | 42 | 64 | | 43 | 3 | | 44 | 83 | | 45 | 25 | | 46 | 4 | | 47 | 2 | | 48 | 59 | | 49 | 24 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 98 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 162 | | matches | | 0 | "wasn't asking" | | 1 | "was waiting" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 139 | | ratio | 0 | | matches | (empty) | |
| 99.92% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 923 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 37 | | adverbRatio | 0.04008667388949079 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.0065005417118093175 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 139 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 139 | | mean | 9.06 | | std | 7.82 | | cv | 0.863 | | sampleLengths | | 0 | 7 | | 1 | 22 | | 2 | 3 | | 3 | 2 | | 4 | 6 | | 5 | 20 | | 6 | 7 | | 7 | 11 | | 8 | 13 | | 9 | 19 | | 10 | 10 | | 11 | 27 | | 12 | 1 | | 13 | 5 | | 14 | 9 | | 15 | 7 | | 16 | 5 | | 17 | 4 | | 18 | 8 | | 19 | 3 | | 20 | 15 | | 21 | 18 | | 22 | 5 | | 23 | 15 | | 24 | 4 | | 25 | 9 | | 26 | 5 | | 27 | 4 | | 28 | 12 | | 29 | 5 | | 30 | 3 | | 31 | 4 | | 32 | 27 | | 33 | 15 | | 34 | 8 | | 35 | 7 | | 36 | 7 | | 37 | 3 | | 38 | 27 | | 39 | 2 | | 40 | 2 | | 41 | 9 | | 42 | 5 | | 43 | 6 | | 44 | 6 | | 45 | 3 | | 46 | 2 | | 47 | 4 | | 48 | 14 | | 49 | 12 |
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| 48.44% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 11 | | diversityRatio | 0.3381294964028777 | | totalSentences | 139 | | uniqueOpeners | 47 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 84 | | matches | | 0 | "Maybe because she'd dreamed about" | | 1 | "Maybe because his face looked" | | 2 | "Maybe because she was tired" | | 3 | "Instead, he stood in the" |
| | ratio | 0.048 | |
| 5.71% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 45 | | totalSentences | 84 | | matches | | 0 | "She slid the cat off" | | 1 | "She pulled the door open" | | 2 | "His platinum hair was slicked" | | 3 | "He held his ivory cane" | | 4 | "Her name in his voice." | | 5 | "Her hand tightened on the" | | 6 | "He wasn't asking." | | 7 | "He was waiting for her" | | 8 | "She knew him well enough" | | 9 | "She felt her lips thin." | | 10 | "She wasn't sure why." | | 11 | "He didn't move to unlock" | | 12 | "He knew better." | | 13 | "She'd watched those hands do" | | 14 | "She'd also watched them be" | | 15 | "He contained contradictions and she'd" | | 16 | "She crossed her arms." | | 17 | "He straightened, tucking his cane" | | 18 | "His eyes met hers and" | | 19 | "His voice dropped, roughened at" |
| | ratio | 0.536 | |
| 25.48% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 73 | | totalSentences | 84 | | matches | | 0 | "The knock came at half" | | 1 | "Aurora looked up from the" | | 2 | "Someone who knew what they" | | 3 | "She slid the cat off" | | 4 | "The deadbolts turned with their" | | 5 | "She pulled the door open" | | 6 | "Lucien stood in the hallway," | | 7 | "His platinum hair was slicked" | | 8 | "The other eye, the black" | | 9 | "He held his ivory cane" | | 10 | "Her name in his voice." | | 11 | "That accented purr she'd spent" | | 12 | "Her hand tightened on the" | | 13 | "The question was polite but" | | 14 | "He wasn't asking." | | 15 | "He was waiting for her" | | 16 | "She knew him well enough" | | 17 | "Lucien Moreau didn't do vulnerability." | | 18 | "Whatever had brought him here," | | 19 | "She felt her lips thin." |
| | ratio | 0.869 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 84 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 34 | | technicalSentenceCount | 2 | | matches | | 0 | "He held his ivory cane loosely in one hand, the fingers of his other hand resting on the doorframe as if he'd been ready to knock again." | | 1 | "His coat was cold and wet against her shirt but his mouth was warm, his tongue sweeping past her lips with a desperation that made her knees weak." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 13 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 55 | | tagDensity | 0.109 | | leniency | 0.218 | | rawRatio | 0.167 | | effectiveRatio | 0.036 | |